Pathology is the study and diagnosis of diseases by examining body tissues, typically under magnification. Currently, pathologists manually review stained tissue samples on glass slides under an optical microscope to render a diagnosis. Tissue samples are typically prepared with stains by a specialist called a histotechnician. Today, pathologists use an optical microscope to look at slides of tissue samples. This process has not changed much in over 100 years. Due to this manual process, the initial diagnosis and subsequent second opinions may be delayed as the correct slides must be physically delivered to the proper pathologist.
Digitizing the tissue sample images enables easier and faster evaluation without the organization, shipment and management of glass slides. Using digital pathology techniques will speed turnaround time and improve pathologists' overall diagnostic processes. In light of mounting healthcare cost pressures and the pervasive need to digitize a patient's medical record place such techniques and solutions in high demand. This area of digital pathology is known as Whole Slide Imaging (WSI) in which entire slides are digitally scanned so that they can be viewed on a computer.
The technology includes the steps of scanning the glass slides that have prepared tissue on them. Since the scanning of the slides is performed at very high resolution, the uncompressed digital output of a slide typically has a very large size, e.g., 10 to 30 GB representing an image that is approximately 40,000 by 40,000 pixels.
The next step in the whole slide imaging scheme is to compress the digital slides. In order to effectively store and stream the digital images, the digital slides must be compressed using lossy compression techniques. The compression algorithm used preferably exhibits high rate-distortion performance, i.e. strong compression with high visual quality. Once compressed, the digital slide images are stored on an image server and streamed to a client viewer located anywhere.
A problem arises in that digital pathology slide images contain significant visual content. This makes the slide images difficult to compress well while maintaining high visual quality at the same time.
Thus, there is a need for an optimized image compression mechanism that is capable of compressing large digital pathology slide images with considerable visual content while maintaining high visual quality.